A robust evaluation of the safety and effectiveness of a medical device under regulatory review is sometimes facilitated with a well-designed meta-analysis to combine and integrate comparable studies of the device identified through systematic review. However, many challenges may have to be overcome for a meta-analysis to be interpretable and generalizable. For example, a literature search to identify studies of the device may be subject to publication bias. When selecting which identified studies to include or not include in a meta-analysis, study evaluators may need to be masked to aspects of the publications including authors, direction of study results, etc. Selected studies may exhibit heterogeneity in study population (enrollment criteria), design, conduct, and analysis, creating difficulties in interpretation and generalizability of the combined analysis. Quality assessment of selected studies can be crucial, including study design (blinding, randomization, control group, patient selection), conduct (missing data), and data available (individual or aggregate). In this talk I’ll discuss these issues in the context of using a meta-analysis for regulatory decision making for medical devices.